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ATAL
2010
Springer
13 years 10 months ago
High-level reinforcement learning in strategy games
Video games provide a rich testbed for artificial intelligence methods. In particular, creating automated opponents that perform well in strategy games is a difficult task. For in...
Christopher Amato, Guy Shani
CVPR
2010
IEEE
14 years 5 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
ICML
2006
IEEE
14 years 10 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto
NIPS
1996
13 years 11 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
IJKL
2008
106views more  IJKL 2008»
13 years 9 months ago
Activity- and taxonomy-based knowledge representation framework
: Elaborations of Competence-based Knowledge Space Theory (CbKST) incorporate skills that refer to the conceptual information of the domain as well as to the activities learners ar...
Birgit Marte, Christina M. Steiner, Jürgen He...